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        "author": "Lars Klitzke",
        "author_email": "Lars.Klitzke@gmail.com",
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        "classifiers": [
            "Intended Audience :: Information Technology",
            "Intended Audience :: Manufacturing",
            "Intended Audience :: Science/Research",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Unix Shell",
            "Topic :: Scientific/Engineering :: Information Analysis"
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        "description": "# DAGMaR: A DAG-based Robust Road Estimation Framework for Scenario Mining\n\n[![pipeline status](https://gitlab.klitzke-web.de/lkl/dagmar/badges/master/pipeline.svg)](https://gitlab.klitzke-web.de/lkl/dagmar/commits/master)\n[![coverage report](https://gitlab.klitzke-web.de/lkl/dagmar/badges/master/coverage.svg)](https://gitlab.klitzke-web.de/lkl/dagmar/commits/master)\n\nThis project provide the software for the algorithms and concepts for enriching real-world test drive data collected within the research project [FASva](https://www.hs-emden-leer.de/en/faculties/faculty-of-technology/projects/fasva/) with information of the road infrastructure as basis for context-aware scenario mining\n\nFor that purpose, the work proposes an advances map matching algorithm that is based on particle filter for vehicle localization employing a directed acyclic graph of mapped roads (*DAGMaR*) to robustly estimate the trajectory of most likely vehicle poses. \n\n## Content\n\nThe `dagmar` package contains the following modules\n\n* `core`: The core functionality including updating the particle filter or the implementation of `DAGMaR`.\n* `io`: Everything file or logging-based related, e.g. progress bars using [tqdm](https://github.com/tqdm/tqdm), saving the state of the particle filter or `DAGMaR`, etc.\n* `location`: That module contains function and classes for handling GPS and UTM locations, and `OSM` as an interface to `overpy` to query OpenStreetMap via Overpass.\n* `move`:  The first step of the processing cycle: move the particle field\n* `weight`: The second step of the processing cycle: weight the particle field\n* `resample`: The last step of the processing cycle: resample the particle field\n* `visualization`: Functions and classes for showing the particle field state\n\n## Installation\n\nEither clone this project with\n\n```bash\ngit clone https://github.com/larsklitzke/dagmar\n```\n\nto extend the functionality of the project or, since the the project is hosted on PyPi, install it with\n\n```bash\npip install dagmar\n```\n\n## Tools\n\nAfter installing the package, the following programs are available for processing and evaluating a conducted drive.\n\n* `dagmar`: Process and evaluate a drive\n* `dagmar-analyse`: Analyze the results of the `Particle cluster` and `DAGMaR` \n* `dagmar-process-pf`: Reconstruct `DAGMaR` based on previously estimated mapped vehicle poses by the `Particle cluster`.\n\n## Dependencies\n\nThis project uses various libraries some of which are listed in the following\n\n* [*Numba*](https://numba.pydata.org/) which is based on [*NumPy*](https://numpy.org/) is used for the particle filter enabling high performance computation.\n* [*seaborn*](https://seaborn.pydata.org/) and [*matplotlib*](https://matplotlib.org/) for visualization\n* [*NetworkX*](https://networkx.github.io/) for the implementation of `DAGMaR`\n* [*Pandas*](https://pandas.pydata.org/) for data management and analysis\n* [*tqdm*](https://github.com/tqdm/tqdm) to show the progress of provided tools via progress bars.\n\n## License\n\nCopyright (C) 2019  Lars Klitzke, Lars.Klitzke@gmail.com\n\nThis program is free software: you can redistribute it and/or modify\nit under the terms of the GNU General Public License as published by\nthe Free Software Foundation, either version 3 of the License, or\n(at your option) any later version.\n\nThis program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\nGNU General Public License for more details.\n\nYou should have received a copy of the GNU General Public License\nalong with this program.  If not, see <http://www.gnu.org/licenses/>.\n\n",
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